ORIGINAL RESEARCH article
Front. Educ.
Sec. Assessment, Testing and Applied Measurement
Volume 10 - 2025 | doi: 10.3389/feduc.2025.1614673
AI vs. Teacher Feedback on EFL Argumentative Writing: A Quantitative Study
Provisionally accepted
- 1Yarmouk University, Irbid, Irbid, Jordan
- 2The University of Jordan, Aljubeiha, Amman, Jordan
- 3Rabdan Academy, Abu Dhabi, United Arab Emirates
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This study investigates the effectiveness of AI-generated feedback compared to teacher-generated feedback on the argumentative writing performance of English as a Foreign Language (EFL) learners at different proficiency levels. Sixty undergraduate students from a writing-focused EFL course in Jordan participated in a quasi-experimental, pretest-posttest study. Participants were stratified into two ACTFL proficiency levels (Intermediate-Low and Advanced-Low) and assigned to either an AI feedback group or a teacher feedback group. Students completed an argumentative writing task, received feedback based on their group, and revised their essays accordingly. An analytic rubric was used to assess writing performance, and inter-rater reliability was established on a stratified 30% subsample to support the validity of the scoring process, with pre-and posttest scores analyzed for gains. Results showed significant improvement in writing performance across all groups, regardless of feedback source or proficiency level. Importantly, no statistically significant difference was found between the AI and teacher feedback groups, and the effect size for this comparison was small (Cohen's d = 0.10). A two-way ANOVA revealed a significant main effect for proficiency level but no significant interaction between feedback type and proficiency. Intermediate-Low learners demonstrated the greatest within-group gains, suggesting that both feedback types were particularly impactful for lower-proficiency students. The findings underscore the potential of large language models (LLMs), when carefully scaffolded and ethically deployed, to support writing development in EFL contexts. AI-generated feedback may serve as a scalable complement to teacher feedback in large, mixed-proficiency classrooms, particularly when guided by well-developed prompts and pedagogical oversight.
Keywords: AI-generated feedback, Argumentative writing, EFL learners, language proficiency, Large Language Models (LLMs), Second language writing, Educational Technology, mixedproficiency classrooms
Received: 22 Apr 2025; Accepted: 30 Jun 2025.
Copyright: © 2025 Alnemrat, Aldamen, Almashour, Al-Deaibes and AlSharefeen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mutasim Al-Deaibes, Yarmouk University, Irbid, 21163, Irbid, Jordan
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